As there are many moving parts on a given construction site, there are also many contractors serving distinct roles with various responsibilities. Particularly, a general contractor needs to know and keep track of a variety of details throughout the length of the project such as acquiring building permits, site surveying, managing personnel and subcontractors, and waste management.
When planning for these and other to-do list items, a seasoned contractor can move forward understanding what will likely happen next based on past experiences. Of course, there are many situations that are unpredictable, where even the most experienced professional can only guess what will happen, as he doesn't have access to all the hidden information across the project. This is increasingly becoming known as the digital "dark data" that can be found in almost every function during building production.
So, what is this "dark data"? Gartner defines dark data as the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes. It’s estimated that companies only use or tap into about 1% of the dark data that they have and store. In construction, the problem with dark data is that the industry doesn’t access, much less realize its value. According to a white paper from FMI, 95% of all data captured in the construction and engineering industry goes unused.
It is easy to understand why data can become dark, but how can seeing it make a difference for a contractor?
Though there are many things a general contractor needs to juggle, there are some common ones that all of them face, regardless of the particulars of a construction site. Typically this might include:
Access to this dark data can make a world of difference in both managing the flow of information and using it to determine what the next steps should be for various site initiatives. Imagine a scenario where a contractor has access to modern tools, such as AI and machine learning, and is able to use these tools to access dark data and then apply it to other real time data, such as traffic and weather. It might work out like this scenario:
Building A is being built, the schedule is approved, and the land is leveled and ready to go. The process of pouring the concrete for the first platform level is in the schedule and has a start date. The construction team can use AI to track and predict weather and traffic patterns around the site, so it is then possible to coordinate all the people, equipment and resources so that they are ready for anything on the day of the pour.
